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本文在Huang等人（1995）提出的随机爬山法（SHC）基础上，使用Ingber（1993）给出的依赖于温度的似Cauchy分布产生的新模型，构造一种叠后地震道及演的新随机爬山法。此法的基本思路是将目标函数定义为归一化的相似系数E，通过SHC法反演得到一个波阻抗模型使E达到极大值。此法在每次迭代构造新模型时，既能在高温时进行稀疏点搜索，又能在低温时于当前模型进行搜索，从而加快了迭代和收敛速度。文中通过对实际声波测井曲线进行SHC反演，采用有、无噪声两种情况，经过44次迭代，相似系数E达到0．99，不论有、无噪声，反演结果均与实际曲线非常接近。该法不仅可以反演出高分辨率的波阻抗剖面，而且可以用于反演孔隙率参数。
Based on the SHC proposed by Huang et al. (1995), a new model of temperature-dependent Cauchy distribution given by Ingber (1993) is used to construct a post-stack seismic trace Random climbing. The basic idea of this method is to define the objective function as the normalized similarity coefficient E and obtain a wave impedance model by Eq. This method accelerates iteration and convergence by constructing a new model for each iteration, searching for sparse points at high temperatures and searching the current model at low temperatures. In this paper, the actual acoustic logging curve is subjected to SHC inversion with and without noise. After 44 iterations, the similarity coefficient E reaches 0.99. The results of the inversion are very close to the actual curves . This method not only can invert the high resolution wave impedance profile, but also can be used to retrieve the porosity parameters.